import face_recognition
import cv2
import numpy as np
import time
import utils
import pyautogui

"""
https://github.com/ageitgey/face_recognition/blob/master/examples/facerec_from_webcam_faster.py

pip install pygame -i https://pypi.tuna.tsinghua.edu.cn/simple

pip install playsound --trusted-host mirrors.tools.huawei.com -i http://mirrors.tools.huawei.com/pypi/simple
"""

# This is a demo of running face recognition on live video from your webcam. It's a little more complicated than the
# other example, but it includes some basic performance tweaks to make things run a lot faster:
#   1. Process each video frame at 1/4 resolution (though still display it at full resolution)
#   2. Only detect faces in every other frame of video.

# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
# specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.


# Load a sample picture and learn how to recognize it.
obama_image = face_recognition.load_image_file("aobama.JPG")
obama_face_encoding = face_recognition.face_encodings(obama_image)[0]

# Load a second sample picture and learn how to recognize it.
biden_image = face_recognition.load_image_file("baidegn.JPG")
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]

yoyo_image = face_recognition.load_image_file("youyou1.JPG")
yoyo_face_encoding = face_recognition.face_encodings(yoyo_image)[0]

# Create arrays of known face encodings and their names
known_face_encodings = [
    obama_face_encoding,
    biden_face_encoding,
    yoyo_face_encoding
]
known_face_names = [
    "Barack Obama",
    "Joe Biden",
    "yoyo"
]

# Initialize some variables
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True

video_capture = cv2.VideoCapture(0)
has_release=False

utils.screenOff()
while True:
    if has_release==True:
        video_capture = cv2.VideoCapture(0)
        has_release=False

    # Grab a single frame of video
    ret, frame = video_capture.read()
    print(ret)

    mark=False

    # Only process every other frame of video to save time
    if process_this_frame:
        # Resize frame of video to 1/4 size for faster face recognition processing
        small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)

        # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
        rgb_small_frame = small_frame[:, :, ::-1]

        # Find all the faces and face encodings in the current frame of video
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)

        face_names = []
        for face_encoding in face_encodings:
            # See if the face is a match for the known face(s)
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
            name = "Unknown"

            # # If a match was found in known_face_encodings, just use the first one.
            # if True in matches:
            #     first_match_index = matches.index(True)
            #     name = known_face_names[first_match_index]

            # Or instead, use the known face with the smallest distance to the new face
            face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
            best_match_index = np.argmin(face_distances)
            if matches[best_match_index]:
                name = known_face_names[best_match_index]

                # 检测到特定对象的时候打开浏览器
                if name == "yoyo":
                    utils.say("扫描到目标柚柚准备打开屏幕")
                    time.sleep(2)

                    # 点亮屏幕
                    # utils.light_or_black_screen()
                    # time.sleep(5)
                    # pyautogui.press('enter')
                    # time.sleep(6)
                    # utils.say("已经打开屏幕准备程序")

                    # 先关闭摄像头，不然浏览器会调用不了
                    video_capture.release()
                    cv2.destroyAllWindows()
                    has_release=True

                    # 发邮件通知入会
                    utils.say("先要通知老爸入会请稍等")
                    time.sleep(2)
                    utils.send_mail()
                    time.sleep(2)
                    utils.say("已经通知完成")

                    # 打开链接
                    time.sleep(2)
                    utils.say("再准备打开浏览器")
                    utils.openURL("https://brtc.cdn.bcebos.com/brtc.html?a=xxxx=8888")
                    utils.say("早发白帝城")
                    time.sleep(2)

                    # 点击进入会议
                    utils.retry_click("out")
                    utils.say("当前柚柚已经进入会议中老爸马上就来请稍等")
                    time.sleep(2)

                    # 只能视频这么久的时间，到期就点击退出
                    time.sleep(300)
                    # 点击退出会议
                    utils.say("远程时间到了即将退出")
                    utils.retry_click("in")
                    time.sleep(7)
                    utils.screenOff()

                    mark=True

                    # 或安装直接将interl浏览器关闭掉
                    # subprocess.run('taskkill /F /IM msedge.exe', shell=True)

                    break
    if mark==False:
        # 如果没有匹配的指定的人脸，就直接显示摄像头内容
        cv2.imshow('Video', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

